It’s becoming more apparent that the “new model” of “big biology”—that is cutting edge experimentation—will follow a lot of the more established “big physics” models in some respects. Big science is big science.
The trend in some of the big institutes like Broad has PIs in charge of large labs, postdocs and graduate students mixed with semi-permanent Masters-level technician staff to provide services from information management and data mining to lab maintenence and experimentation. The bigger the project, the more important the technical staff will become.
In bioinformatics, if you’ve been checking the job boards, you’ll notice a large number of computer programming and bioinformatics positions coming open in the Boston area, many at Broad and MIT followed closely by jobs in the Longwood area. Typically, their educational requirements are at or below the Masters degree level, following these employment trends.
Over the past five years, we’ve seen increasing trends for large-scale biological experiments and their associated information to become more standardized and less esoteric. Doctoral-level experience is no longer necessary to manage this kind of data or to conceive of interesting in silico experiments to perform on the data. Several of the graduates from the Bioinformatics Masters Degree Program at Brandeis are functioning in these “big science” groupsin exactly that way. Others are in large pharma companies supporting research and information management. Others are working in biology cores in small groups in the Longwood area.
Molecular biology jobs at the Masters degree level do not seem as active on the job boards right now. I believe this will probably change with the continual standardization of experimental procedures and the growth of standard protocols for in the “big science” models. There is a definite need of chemists and biologists who can adequately design and carry out experiments who nevertheless do not need the training of a PhD to run, say, a bench within a sequencing core or a chemical library database. I don’t pretend to be a fortune teller and you’re right if you think this “prediction” is obvious, but it appears that as biology gets bigger and more centralized, chemists and biologists with Masters degrees will find themselves more in demand around the Boston area.
Biostatistics is still pretty much a doctoral-level type of job at this point. This is for several reasons that spiderweb throughout that employment market, including the necessity of trained people in clinical trials and some of the difficulties in addressing standard types of educational needs at the Masters level. However, I predict that there will be a growing need for trained Masters-level medical informatics and clinical informatics technicians within the next few years. As the number of clinical trials grow, so will the need to tie that information back into drug discovery projects, and the federation of existing bioinformatics and chemical databases with medical and clinical trial data will be necessary. It’s on the horizon now.
Another lesser-known area that I believe will grow and diversify is the “chemoinformatics” area. Although this field is currently closely tied with structural biology, I believe that there is room for Masters-level trained chemists-slash-programmers to combine their education with experience in structural biology to assist large-scale screening projects as big projects seek to explore chemical space in everything from cancer to parasite biology.
So what’s your advice for bioinformatics/biostats people at the master’s level? Get a job or continue with a PhD? What kind of career growth opportunities will be there for someone with “just” a Master’s?
Corie wrote:
So what’s your advice for bioinformatics/biostats people at the master’s level? Get a job or continue with a PhD?
I believe this is a great time for Masters-level technical scientists in biotech across academia, government, and industry, even if the scientist is deciding to take a stopping point before moving onward with a PhD. The hierarchies that will define career paths for Masters-level scientists in the bioinfo/biostats/chemoinfo/stats technical fields are still being defined. It’s recognized widely that a well-trained Masters-level scientist can perform many if not all of the same kinds of tasks a PhD can. There seem to be more Masters-level jobs in the Boston area right now than there are jobs that specifically ask for a PhD.
One of the contributing reasons for my sunny view for a terminal Masters degree is that many biological or chemical scientists are still receiving doctorates without any kind of statistical, computational or IT backgrounds. Most of the more sophisticated questions in drug discovery or genomics research are based in large-scale data analysis, such as in re-sequencing of human populations, or screening compounds against a series of parasites, or looking at epigenetic changes across cancer types. Institutions or companies that plan on that kind of project sophistication need scientists who have skills in computational data analysis as well as biology, yet many educational programs are still graduating their scientists without those skills. Additionally, there is no specific need for every scientist in these projects to be master of all techniques. The solution is to allow necessary skill sets to come from outside a typical PhD-level education. The specialized skills that focused Masters-level scientists can bring into a research environment are a great value for the money for these institutions.
It can be easily argued that a PhD project director who is paid and trained to conceive, lead, and execute sophisticated research projects should be able to give the number-crunching and data-crunching jobs to people who are devoting their career to perfecting those skills. The PhD may need to understand or even direct the activity, but it’s more efficient for the project director to assemble a team that includes Masters-level specialists to provide standardized methodologies and platform consistency.
What kind of career growth opportunities will be there for someone with “just” a Master’s?
The answer depends on the student’s career aspirations and what kind of employer they work for.
There is an absolutely positive precedent for a terminal Masters in IT/CS and engineering. The disciplines I mention in my earlier article are very much in the same spirit as those terminal Masters degrees although they are hybridized with the natural sciences. I feel that the career opportunities for well-trained Masters-level technical scientists can track along with engineering or IT/CS careers.
A person interested in advancing within a specific institution should ask what the company’s policy is regarding educational level and advancement. For instance, if a Masters-level person is hired by a biopharmaceutical company, the policies at that company are what determines the potential career paths for a terminal Masters education. Many companies are inclusive of Masters-level people with experience commensurate with PhD-level work, so career paths for technical Masters degrees within small to mid-range biopharmaceutical companies are usually less rigidly defined. Larger pharmas often have written rules for advancement (ie, PhDs are the only ones able to hold positions above a certain level). The candidate should be asking these questions as part of their interview.
The Masters-level person will not command as high a salary as a seasoned PhD, but they certainly will earn more than postdoctoral scientists, and I know of at least two biotech companies that have group leaders among their ranks who have Masters-level educations. A highly skilled Masters-level technical scientist who also has good communication and teamwork skills should have no problem finding employment now or in the future as far as I can see. If that person wants to move on to directing scientific projects, they should carefully consider a PhD in a strong well-funded laboratory. It should also be mentioned that many employers have provisions for education parallel with employment, including PhD work, and the cost of that education could be supplemented by the employer as well.
The NSF’s Science and Engineering Indicators 2006 report has a lot of statistics regarding employment of scientists and engineers at various degree levels and also salary levels.
Thanks, Hilary. A lot of the tables in that publication support the idea that technical Masters degrees earn salaries that rival Doctoral degres—I have to look into the tables more and I should blog the results related to this subject.
Your information are of great value to me. I am a pharmacy student interested in IT and genomics. Although my University does not provide exhaustive coverage on that topics I am trying to improve my skills and knowledge in that areas using for instance freely available Internet resources (http://www.oercommons.org/). Have good experience in group management on national level and in international cooperation.
What would you advice to a person like me? What type of firms or research areas should I in your opinion concentrate on? Does the clinical pharmacist position fit to any of career paths proposed by you?
Hi, Janusz…
It’s difficult to see where you “fit” without knowing more about your interests. A general interest in pharmacology, IT and genomics could be used in a number of applications from clinical information management to research. I’ve put a couple of interesting articles here below.
Hospitals move to e-files spurs a labor shortage
Smart Care Via a Mouse, but What Will It Cost?
Hello, Janusz,
Pharmcogenomics is still a very new area. There is no position titled as pharmacogenomist yet. Clinically, testing the genome map of patients is still very expensive. At the present, it is very uncommon for insurance companies to be willing to pay for that kind of testing(Approx. $1000/test). Insurance companies usually makes decisions after they see cost analysis studies. I do not think we have good studies of that sort yet. Therefore, integrating pharmacogenomics in actual pharmacy practice is still years away.
If you are interested in this area, I will advise you to pursue a PhD. Check if your pharmacy schools offer PharmD/PhD programs. That may save you time. As mentioned by Deanne, statistic skill and computer skills are very important in genome analysis for number crunching. If you decide to pursue a MS after your PharmD, a degree in MS Statistics or molecular/computational biology will be helpful. One thing to keep in mind is that you may want to go on a path that leverages the synergy between your PharmD education and any extra training you embark upon so you do not end up giving up the return of your time and monetary investments.